DoS攻击下基于APF和DDPG算法的无人机安全集群控制  

Secure cluster control of UAVs under DoS attacks based on APF and DDPG algorithm

作　　者：林柄权 刘磊[1] 李华峰[2] 刘晨[1] LIN Bingquan;LIU Lei;LI Huafeng;LIU Chen(School of Mathematics,Hohai University,Nanjing Jiangsu 211100,China;Department of Computer Science and Technology,Tangshan Normal University,Tangshan Hebei 063000,China)

机构地区：[1]河海大学数学学院,南京211100 [2]唐山师范学院计算机科学技术系,河北唐山063000

出　　处：《计算机应用》2025年第4期1241-1248,共8页journal of Computer Applications

基　　金：河北省自然科学基金资助项目(A2023209002);安徽省重点实验室基金资助项目(KLAHEI18018);教育部重点实验室开放基金资助项目(Scip20240111)。

摘　　要：针对拒绝服务(DoS)攻击下无人机(UAV)通信阻塞、运动轨迹不可预测的问题,在人工势场法(APF)和深度确定性策略梯度(DDPG)融合框架下研究DoS攻击期间的多UAV安全集群控制策略。首先,使用Hping3对所有UAV进行DoS攻击检测,以实时确定UAV集群的网络环境;其次,当未检测到攻击时,采用传统的APF进行集群飞行;再次,在检测到攻击后,将被攻击的UAV标记为动态障碍物,而其他UAV切换为DDPG算法生成的控制策略;最后,所提框架实现APF和DDPG的协同配合及优势互补,并通过在Gazebo中进行仿真实验验证DDPG算法的有效性。仿真实验结果表明,Hping3能实时检测出被攻击的UAV,且其他正常UAV切换为DDPG算法后能稳定避开障碍物,从而保障集群安全;在DoS攻击期间,采用切换避障策略的成功率为72.50%,远高于传统APF的31.25%,且切换策略逐渐收敛,表现出较好的稳定性;训练后的DDPG避障策略具有一定泛化性,当环境中出现1~2个未知障碍物时仍能稳定完成任务。Addressing the issues of communication obstruction and unpredictable motion trajectories of Unmanned Aerial Vehicles(UAVs)under Denial of Service(DoS)attacks,research was conducted on the secure cluster control strategy for multi-UAV during DoS attacks within a framework that integrates Artificial Potential Field(APF)and Deep Deterministic Policy Gradient(DDPG)algorithm.Firstly,Hping3 was utilized to detect DoS attacks on all UAVs,thereby determining the network environment of the UAV cluster in real time.Secondly,when no attack was detected,the traditional APF was employed for cluster flight.After detecting attacks,the targeted UAVs were marked as dynamic obstacles while other UAV switched to control strategies generated by DDPG algorithm.Finally,with the proposed framework,the cooperation and advantage complementary of APF and DDPG were realized,and the effectiveness of the DDPG algorithm was validated through simulation in Gazebo.Simulation results indicate that Hping3 can detect the UAVs under attack in real time,and other normal UAVs can avoid obstacles stably after switching to DDPG algorithm,so as to ensure cluster security;the success rate of the switching obstacle avoidance strategy during DoS attacks is 72.50%,significantly higher than that of the traditional APF(31.25%),and the switching strategy converges gradually,demonstrating a pretty stability;the trained DDPG obstacle avoidance strategy exhibits a degree of generalization,capable of completing tasks stably with 1 to 2 unknown obstacles appeared in the environment.

关 键 词：无人机集群 人工势场法 深度确定性策略梯度 切换策略 网络安全 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]